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Universality is one of the key concepts in understanding critical phenomena. However, for interacting inhomogeneous systems described by complex networks a clear understanding of the relevant parameters for universality is still missing.…

Statistical Mechanics · Physics 2021-04-22 Ana P. Millán , Giacomo Gori , Federico Battiston , Tilman Enss , Nicolò Defenu

We consider propagation models that describe the spreading of an attribute, called "damage", through the nodes of a random network. In some systems, the average fraction of nodes that remain undamaged vanishes in the large system limit, a…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Björn Samuelsson , Joshua E. S. Socolar

Percolation theory is extensively studied in statistical physics and mathematics with applications in diverse fields. However, the research is focused on systems with only one type of links, connectivity links. We review a recently…

Statistical Mechanics · Physics 2015-05-28 Amir Bashan , Shlomo Havlin

We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another…

Social and Information Networks · Computer Science 2020-05-22 Jan Overgoor , Austin R. Benson , Johan Ugander

Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This…

Disordered Systems and Neural Networks · Physics 2015-06-25 Albert-Laszlo Barabasi , Reka Albert

This paper investigates the approximation power of three types of random neural networks: (a) infinite width networks, with weights following an arbitrary distribution; (b) finite width networks obtained by subsampling the preceding…

Machine Learning · Computer Science 2019-10-21 Bolton Bailey , Ziwei Ji , Matus Telgarsky , Ruicheng Xian

We constructs a new network by superposition of hexahedron , which are scale-free, highly sparse,disassortative ,and maximal planar graphs. The network degree distribution, agglomeration coefficient and degree of correlation are computed…

Physics and Society · Physics 2021-04-12 Li Haijun , Lu Qingping

Various approaches and measures from network analysis have been applied to granular and particulate networks to gain insights into their structural, transport, failure-propagation and other systems-level properties. In this article, we…

Soft Condensed Matter · Physics 2019-11-06 Silvia Nauer , Lucas Böttcher , Mason A. Porter

We study the asymptotic performance of two multi-hop overlaid ad-hoc networks that utilize the same temporal, spectral, and spatial resources based on random access schemes. The primary network consists of Poisson distributed legacy users…

Networking and Internet Architecture · Computer Science 2013-06-05 Armin Banaei , Costas N. Georghiades , Shuguang Cui

The equilibrium properties of allocation algorithms for networks with a large number of nodes with finite capacity are investigated. Every node is receiving a flow of requests and when a request arrives at a saturated node, i.e. a node…

Probability · Mathematics 2026-01-14 Davit Martirosyan , Philippe Robert

Network data appear in a number of applications, such as online social networks and biological networks, and there is growing interest in both developing models for networks as well as studying the properties of such data. Since individual…

Machine Learning · Statistics 2016-03-23 Diana Cai , Tamara Broderick

We present a model for the evolution of networks of occupied sites on undirected regular graphs. At every iteration step in a parallel update I randomly chosen empty sites are occupied and occupied sites having degree outside of a given…

Statistical Mechanics · Physics 2009-11-07 M. Brede , U. Behn

Assuming a network of infinite extent, several researchers have analyzed small-cell networks using a Poisson point process (PPP) location model, leading to simple analytic expressions. The general assumption has been that these results…

Information Theory · Computer Science 2015-12-11 S. Alireza Banani , Andrew W. Eckford , Raviraj S. Adve

Complex networks describe a wide range of systems in nature and society. Frequently cited examples include Internet, WWW, a network of chemicals linked by chemical reactions, social relationship networks, citation networks, etc. The…

Physics and Society · Physics 2013-02-26 James Kim

The concept of nestedness, in particular for ecological and economical networks, has been introduced as a structural characteristic of real interacting systems. We suggest that the nestedness is in fact another way to express a mesoscale…

Physics and Society · Physics 2016-02-22 Sang Hoon Lee

We conduct a systematic study of asynchronous models of distributed computing consisting of identical finite-state devices that cooperate in a network to decide if the network satisfies a given graph-theoretical property. Models discussed…

Formal Languages and Automata Theory · Computer Science 2020-07-08 Javier Esparza , Fabian Reiter

Many complex natural and physical systems exhibit patterns of interconnection that conform, approximately, to a network structure referred to as scale-free. Preferential attachment is one of many algorithms that have been introduced to…

Physics and Society · Physics 2014-11-18 Linjun Zhang , Michael Small , Kevin Judd

The problem of joint sequential detection and isolation is considered in the context of multiple, not necessarily independent, data streams. A multiple testing framework is proposed, where each hypothesis corresponds to a different subset…

Statistics Theory · Mathematics 2022-07-04 Anamitra Chaudhuri , Georgios Fellouris

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it…

Social and Information Networks · Computer Science 2014-09-02 Bojin Zheng , Hongrun Wu , Li Kuang , Jun Qin , Wenhua Du , Jianmin Wang , Deyi Li

We study the expressivity of sparse maxout networks, where each neuron takes a fixed number of inputs from the previous layer and employs a, possibly multi-argument, maxout activation. This setting captures key characteristics of…

Machine Learning · Computer Science 2025-10-17 Moritz Grillo , Tobias Hofmann
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